15 citations · 15 across the 8 of their papers we have counts for
8 papers
MR2-ByteTrack: CNN and Transformer-based Video Object Detection for AI-augmented Embedded Vision Sensor Nodes
Luca Bompani, Manuele Rusci, Luca Benini +2
Modern smart vision sensors need on-device intelligence to process video streams, as cloud computing is often impractical due to bandwidth, latency, and privacy constraints. Howeve…
Tiny-DroNeRF: Tiny Neural Radiance Fields aboard Federated Learning-enabled Nano-drones
Ilenia Carboni, Elia Cereda, Lorenzo Lamberti +3
Sub-30g nano-sized aerial robots can leverage their agility and form factor to autonomously explore cluttered and narrow environments, like in industrial inspection and search and…
Multi-modal On-Device Learning for Monocular Depth Estimation on Ultra-low-power MCUs
Davide Nadalini, Manuele Rusci, Elia Cereda +3
Monocular depth estimation (MDE) plays a crucial role in enabling spatially-aware applications in Ultra-low-power (ULP) Internet-of-Things (IoT) platforms. However, the limited num…
Circuits and Systems for Embodied AI: Exploring uJ Multi-Modal Perception for Nano-UAVs on the Kraken Shield
Viviane Potocnik, Alfio Di Mauro, Lorenzo Lamberti +4
Embodied artificial intelligence (AI) requires pushing complex multi-modal models to the extreme edge for time-constrained tasks such as autonomous navigation of robots and vehicle…
Accelerating Image-based Pest Detection on a Heterogeneous Multi-core Microcontroller
Luca Bompani, Luca Crupi, Daniele Palossi +5
The codling moth pest poses a significant threat to global crop production, with potential losses of up to 80% in apple orchards. Special camera-based sensor nodes are deployed in…
Distilling Tiny and Ultra-fast Deep Neural Networks for Autonomous Navigation on Nano-UAVs
Lorenzo Lamberti, Lorenzo Bellone, Luka Macan +4
Nano-sized unmanned aerial vehicles (UAVs) are ideal candidates for flying Internet-of-Things smart sensors to collect information in narrow spaces. This requires ultra-fast naviga…
Combining Local and Global Perception for Autonomous Navigation on Nano-UAVs
Lorenzo Lamberti, Georg Rutishauser, Francesco Conti +1
A critical challenge in deploying unmanned aerial vehicles (UAVs) for autonomous tasks is their ability to navigate in an unknown environment. This paper introduces a novel vision-…
A Sim-to-Real Deep Learning-based Framework for Autonomous Nano-drone Racing
Lorenzo Lamberti, Elia Cereda, Gabriele Abbate +7
Autonomous drone racing competitions are a proxy to improve unmanned aerial vehicles' perception, planning, and control skills. The recent emergence of autonomous nano-sized drone…